WEBVTT 00:00:00.000 --> 00:00:02.339 Have you ever looked at a new AI tool and thought, 00:00:02.940 --> 00:00:05.639 hmm, that's just a simple wrapper around something 00:00:05.639 --> 00:00:09.640 like chat GPT. What if those really simple seeming 00:00:09.640 --> 00:00:12.480 applications are actually hidden gold mines, 00:00:12.859 --> 00:00:15.179 quietly generating millions? It's a natural first 00:00:15.179 --> 00:00:17.280 thought, isn't it? It's easy to dismiss them. 00:00:17.339 --> 00:00:19.239 But what we've kind of discovered is, look, these 00:00:19.239 --> 00:00:21.960 aren't just connecting to an API and slapping 00:00:21.960 --> 00:00:24.940 on a pretty interface. Not at all. They are deeply, 00:00:25.719 --> 00:00:27.980 meaningfully solving real specific problems for 00:00:27.980 --> 00:00:30.960 people. In ways, general AI tools just, they 00:00:30.960 --> 00:00:33.520 can't match. And yeah, some are making genuinely 00:00:33.520 --> 00:00:35.579 incredible revenue. We are talking millions of 00:00:35.579 --> 00:00:38.200 dollars. Serious money. Today we're taking a 00:00:38.200 --> 00:00:41.060 deep dive into precisely that whole phenomenon. 00:00:41.640 --> 00:00:43.200 Our recent research, it's really a collection 00:00:43.200 --> 00:00:46.740 of insights from very successful AI product builders, 00:00:46.859 --> 00:00:49.280 and it challenges that common idea that simple 00:00:49.280 --> 00:00:52.380 AI apps are somehow less valuable. We'll unpack 00:00:52.380 --> 00:00:54.640 why these solutions are thriving, look at some 00:00:54.640 --> 00:00:56.539 fascinating real -world examples that, well, 00:00:56.560 --> 00:00:58.799 I think they'll likely surprise you, and then, 00:00:58.799 --> 00:01:01.320 most importantly, map out a clear path for how 00:01:01.320 --> 00:01:03.619 you could maybe build something similar. It's 00:01:03.619 --> 00:01:05.680 really all about understanding the subtle but 00:01:05.680 --> 00:01:08.000 profound insights hidden beneath the surface 00:01:08.000 --> 00:01:11.299 of what seems simple. So let's really unpack 00:01:11.299 --> 00:01:13.560 this a bit. The initial perception, like we said, 00:01:13.739 --> 00:01:15.799 is that AI wrappers, and just to be clear, we 00:01:15.799 --> 00:01:18.439 mean applications that build a specialized user 00:01:18.439 --> 00:01:21.219 -friendly interface around powerful underlying 00:01:21.219 --> 00:01:24.420 AI models, like OpenAI APIs, right? Tailoring 00:01:24.420 --> 00:01:27.019 them for very specific tasks. Right. Specific 00:01:27.019 --> 00:01:29.719 tasks or workflows. Exactly. The perception is 00:01:29.719 --> 00:01:32.200 that they're simplistic. But our analysis, it 00:01:32.200 --> 00:01:34.680 fundamentally challenges that view. Oh, absolutely. 00:01:34.879 --> 00:01:37.019 These aren't just random apps floating around 00:01:37.019 --> 00:01:39.540 out there, the ones that genuinely succeed. They 00:01:39.540 --> 00:01:43.260 do so by precisely pinpointing these deeply felt 00:01:43.260 --> 00:01:46.760 user struggles, beat. And then crucially, they 00:01:46.760 --> 00:01:49.519 don't just offer an AI answer, they craft an 00:01:49.519 --> 00:01:51.879 incredibly easy to use solution that's smoothed 00:01:51.879 --> 00:01:54.599 out the entire process. They truly solve the 00:01:54.599 --> 00:01:57.019 whole problem, not just offer a little piece 00:01:57.019 --> 00:01:59.739 of it. That's a crucial distinction. So it's 00:01:59.739 --> 00:02:02.120 not really about the raw AI power then, is it? 00:02:02.400 --> 00:02:04.400 So what's the core differentiator we're seeing 00:02:04.400 --> 00:02:06.640 for these successful applications? Simple. They 00:02:06.640 --> 00:02:09.580 solve specific problems with a superior user 00:02:09.580 --> 00:02:12.719 experience. That's basically it. OK. So our research 00:02:12.719 --> 00:02:14.740 points to three fundamental ingredients for a 00:02:14.740 --> 00:02:16.919 success here. It's essentially the bedrock these 00:02:16.919 --> 00:02:19.139 successful companies build upon. Yeah, first, 00:02:19.360 --> 00:02:21.620 you absolutely have to solve a very specific 00:02:21.620 --> 00:02:24.020 problem. Don't try to be everything to everyone. 00:02:24.080 --> 00:02:26.479 That's such a common trap. Instead, pick one 00:02:26.479 --> 00:02:29.560 clear, undeniable pain point that users genuinely 00:02:29.560 --> 00:02:32.659 struggle with. Really narrow it down. Second, 00:02:33.280 --> 00:02:36.840 you must create a superior user experience. Yes, 00:02:37.139 --> 00:02:39.719 OK, your users could go directly to chat GPT 00:02:39.719 --> 00:02:42.639 or whatever, but your wrapper, your tool, it 00:02:42.639 --> 00:02:44.819 has to make the process significantly faster 00:02:44.819 --> 00:02:47.639 or easier or maybe produce a more professional 00:02:47.840 --> 00:02:51.199 tailored output. Think about washing machines. 00:02:51.620 --> 00:02:53.560 You could wash clothes by hand, right? Of course. 00:02:53.900 --> 00:02:56.240 But the convenience, the efficiency of a machine, 00:02:56.479 --> 00:02:58.860 it changed everything. Convenience, specialization, 00:02:59.000 --> 00:03:01.560 and just a seamless flow. That's what wins. OK, 00:03:01.680 --> 00:03:04.039 makes sense. And the third ingredient, it seems 00:03:04.039 --> 00:03:06.080 almost obvious maybe, but it's often overlooked. 00:03:06.360 --> 00:03:09.099 Focus. Focus on a very clear customer type. You 00:03:09.099 --> 00:03:10.599 need to know exactly who you're serving. Like, 00:03:10.599 --> 00:03:12.120 what does their daily life look like? What do 00:03:12.120 --> 00:03:14.699 they truly need? This kind of laser -like clarity, 00:03:14.699 --> 00:03:16.520 it guides everything. The features you build, 00:03:16.580 --> 00:03:18.919 how you price your service, how you market it. 00:03:19.199 --> 00:03:20.879 Without that focus, you're just kind of throwing 00:03:20.879 --> 00:03:23.080 darts in the dark, hoping something sticks. That 00:03:23.080 --> 00:03:25.400 really resonates. But let's linger on that user 00:03:25.400 --> 00:03:29.360 experience point. Why is that superior experience, 00:03:29.500 --> 00:03:31.879 that ease in professionalism, why is that more 00:03:31.879 --> 00:03:35.000 critical than just the raw underlying AI power 00:03:35.000 --> 00:03:38.520 itself? Because it makes complex AI fast, easy, 00:03:38.580 --> 00:03:40.659 and professional for the user. Right. Let's make 00:03:40.659 --> 00:03:42.460 this concrete. Let's look at some real -world 00:03:42.460 --> 00:03:46.259 examples. Our first one, SheetsResume .com. It 00:03:46.259 --> 00:03:48.879 targets individual job seekers, right? An AI 00:03:48.879 --> 00:03:51.199 -powered resume builder. And here's where it 00:03:51.199 --> 00:03:53.960 gets really interesting for me. The founder wasn't 00:03:53.960 --> 00:03:56.939 just some tech person. They were actually a former 00:03:56.939 --> 00:03:59.620 recruiter. That deep inside knowledge, that was 00:03:59.620 --> 00:04:01.419 a massive advantage. Exactly. They understood 00:04:01.419 --> 00:04:03.259 the nuances, the little things recruiters look 00:04:03.259 --> 00:04:05.460 for. So users just connect their LinkedIn profile, 00:04:05.580 --> 00:04:08.159 pretty simple, and the AI goes to work. It pulls 00:04:08.159 --> 00:04:10.800 the relevant info and then writes these compelling 00:04:10.800 --> 00:04:13.139 industry -specific bullet points. It totally 00:04:13.139 --> 00:04:16.319 removes that agonizing, staring at a blank document 00:04:16.319 --> 00:04:18.819 headache we've all had. That founder's specialized 00:04:18.819 --> 00:04:21.480 domain knowledge, that became their unique competitive 00:04:21.480 --> 00:04:23.660 advantage. It's huge. Mm -hmm. And they operate 00:04:23.660 --> 00:04:26.800 in this massive B2C market, right? A huge potential 00:04:26.800 --> 00:04:29.740 audience. But the need isn't typically recurring. 00:04:29.839 --> 00:04:32.279 You only update your resume every few years, 00:04:32.339 --> 00:04:34.879 maybe. So how did they crack the pricing strategy 00:04:34.879 --> 00:04:36.839 for what seems like a non -recurring problem? 00:04:36.959 --> 00:04:40.199 Ah, good question. They charge a $99 one -time 00:04:40.199 --> 00:04:43.720 fee. Lifetime access. Now think about it from 00:04:43.720 --> 00:04:46.579 the jobseeker's perspective. Landing a better 00:04:46.579 --> 00:04:49.060 job, or even just getting interviews faster. 00:04:49.439 --> 00:04:52.740 That $99 becomes a phenomenal return on investment. 00:04:53.120 --> 00:04:55.220 A no -brainer, really. It's a single payment 00:04:55.220 --> 00:04:57.339 that perfectly suits the non -recurring nature 00:04:57.339 --> 00:04:59.959 of the core problem they solve. It's smart. It's 00:04:59.959 --> 00:05:02.339 about the value provided, not just raw usage 00:05:02.339 --> 00:05:04.660 metrics. And the numbers for Sheet's resume are 00:05:04.660 --> 00:05:07.740 pretty compelling. They see around 135 ,000 monthly 00:05:07.740 --> 00:05:10.180 visitors. Now, even if you take a conservative 00:05:10.180 --> 00:05:13.480 conversion rate, say... 0 .5%. That still suggests 00:05:13.480 --> 00:05:16.759 over $66 ,000 in monthly revenue, though they've 00:05:16.759 --> 00:05:19.019 apparently reported closer to $20 ,000, which 00:05:19.019 --> 00:05:21.160 is still a very significant income for such a 00:05:21.160 --> 00:05:23.240 specialized tool. All right, then $20K is nothing 00:05:23.240 --> 00:05:25.939 to sneeze at. But here's the true genius, I think. 00:05:26.680 --> 00:05:29.240 They didn't just stop at resumes, they expanded, 00:05:29.620 --> 00:05:33.310 but thoughtfully. Now they offer AI cover letters, 00:05:33.730 --> 00:05:35.990 tools for mock interviews, even an AI -powered 00:05:35.990 --> 00:05:38.689 job board. They understood their customer deeply, 00:05:39.009 --> 00:05:41.370 saw the whole journey, and decided to build a 00:05:41.370 --> 00:05:43.889 comprehensive solution around that entire job 00:05:43.889 --> 00:05:46.310 application process, not just that one initial 00:05:46.310 --> 00:05:49.019 step. Very smart expansion. So thinking about 00:05:49.019 --> 00:05:51.079 that pricing model again, what's the biggest 00:05:51.079 --> 00:05:53.800 lesson we can maybe take away from Sheet's resume's 00:05:53.800 --> 00:05:55.579 strategy? Price for the value to the customer, 00:05:55.759 --> 00:05:57.560 not just the recurring need. OK, let's shift 00:05:57.560 --> 00:06:01.160 gears. Our next example is cuppa .ai. This one 00:06:01.160 --> 00:06:04.160 tackles the complex challenge of content creation, 00:06:04.220 --> 00:06:05.899 but for businesses. So we're talking not just 00:06:05.899 --> 00:06:08.019 writing one article, but creating a lot of content 00:06:08.019 --> 00:06:10.819 consistently and often at scale. Yeah. And this 00:06:10.819 --> 00:06:13.439 is where that whole wrapper concept really, really 00:06:13.439 --> 00:06:16.759 shines for B2B for businesses. Sure. Okay. But 00:06:16.759 --> 00:06:18.879 marketing team could use ChatGPT directly to 00:06:18.879 --> 00:06:22.480 draft some articles. Fine. But Kappa AI, it offers 00:06:22.480 --> 00:06:24.920 a complete system. You upload your brand guidelines, 00:06:25.019 --> 00:06:27.480 your voice, all that stuff, and then it can generate 00:06:27.480 --> 00:06:29.480 hundreds of articles with a consistent tone. 00:06:29.759 --> 00:06:32.579 Then, and this is key, it can publish them directly 00:06:32.579 --> 00:06:35.800 to WordPress, handle the SEO optimization, even 00:06:35.800 --> 00:06:38.199 help manage content calendars. It's a workflow 00:06:38.199 --> 00:06:40.149 tool. It really is like the difference between, 00:06:40.149 --> 00:06:42.589 say, cooking one meal for yourself versus running 00:06:42.589 --> 00:06:44.610 a full service restaurant kitchen, isn't it? 00:06:44.790 --> 00:06:47.430 Kappa AI manages that whole complex workflow. 00:06:47.769 --> 00:06:49.870 Exactly. That's a great analogy. And they've 00:06:49.870 --> 00:06:52.069 clearly targeted small businesses, maybe marketing 00:06:52.069 --> 00:06:54.470 agencies or even solo content creators, basically 00:06:54.470 --> 00:06:57.170 customers with ongoing repetitive needs. Content 00:06:57.170 --> 00:06:59.509 is constant for them. So this makes a subscription 00:06:59.509 --> 00:07:01.990 model absolutely perfect. They have like. 25 00:07:01.990 --> 00:07:05.110 or $60 monthly plans, and they cleverly highlight 00:07:05.110 --> 00:07:08.009 that $60 plan, which is, you know, a classic 00:07:08.009 --> 00:07:10.769 psychological pricing tactic. It gently guides 00:07:10.769 --> 00:07:12.730 users towards the more comprehensive offering. 00:07:13.230 --> 00:07:17.069 Right. And cuppa .ai sees around 40 ,000 monthly 00:07:17.069 --> 00:07:20.629 visitors. Their estimated monthly recurring revenue, 00:07:20.829 --> 00:07:23.509 based on that traffic, is maybe around $18 ,000. 00:07:23.949 --> 00:07:26.069 Although, interestingly, their actual reported 00:07:26.069 --> 00:07:28.750 revenue is closer to $30 ,000. Yeah. And that 00:07:28.750 --> 00:07:31.740 higher actual revenue, it really They've got 00:07:31.740 --> 00:07:33.560 either better conversion rates than we estimated 00:07:33.870 --> 00:07:36.370 or maybe just fantastic customer attention. People 00:07:36.370 --> 00:07:39.209 stick around. And this model works precisely 00:07:39.209 --> 00:07:41.709 because it's not just about content generation. 00:07:41.829 --> 00:07:44.810 It's a complete content workflow solution. That 00:07:44.810 --> 00:07:47.370 WordPress integration alone, that probably saves 00:07:47.370 --> 00:07:49.850 their customers hours every single week. It streamlines 00:07:49.850 --> 00:07:52.189 what can be a really messy time -consuming process. 00:07:52.449 --> 00:07:54.949 That's real tangible value right there. So how 00:07:54.949 --> 00:07:57.529 does Kappa AI specifically exemplify that core 00:07:57.529 --> 00:07:59.949 idea we keep mentioning, solving the whole problem? 00:08:00.050 --> 00:08:02.610 It integrates content creation, branding, SEO, 00:08:03.029 --> 00:08:06.769 and Okay, now for perhaps the most surprising 00:08:06.769 --> 00:08:08.810 and frankly biggest success story we came across. 00:08:09.160 --> 00:08:12.279 ATHOR. This is an AI writing assistant, but it's 00:08:12.279 --> 00:08:14.240 specifically focused on academic research. And 00:08:14.240 --> 00:08:17.000 when we say success, we mean over a million dollars 00:08:17.000 --> 00:08:20.180 in monthly revenue. That's just a truly staggering 00:08:20.180 --> 00:08:22.800 figure for what seems like a very niche AI tool. 00:08:22.939 --> 00:08:25.480 It really is. But this is hyper specialization 00:08:25.480 --> 00:08:28.120 executed perfectly. Think about academic writing. 00:08:28.379 --> 00:08:31.160 It has incredibly specific, often kind of daunting 00:08:31.160 --> 00:08:34.240 requirements, right? Precise citation formats 00:08:34.240 --> 00:08:37.620 like MLA or APA, complex research integration, 00:08:38.019 --> 00:08:41.100 very formal. structures, specific academic language, 00:08:41.419 --> 00:08:44.120 and it's also a massive global market. Millions 00:08:44.120 --> 00:08:45.980 of college students, grad students, professional 00:08:45.980 --> 00:08:47.960 researchers worldwide, all these individuals 00:08:47.960 --> 00:08:50.500 constantly need to write papers, essays, theses 00:08:50.500 --> 00:08:52.840 with proper citations. It's a constant pressure. 00:08:53.080 --> 00:08:54.740 The numbers are, well they're frankly hard to 00:08:54.740 --> 00:08:57.419 wrap your head around, 1 .3 million monthly visitors 00:08:57.419 --> 00:08:59.620 and at an average price point of around $20 per 00:08:59.620 --> 00:09:02.710 month. Yeah. Do the math. That's how you get 00:09:02.710 --> 00:09:05.429 to over $1 million in monthly recurring revenue. 00:09:05.750 --> 00:09:08.029 Just incredible. And their marketing strategy 00:09:08.029 --> 00:09:12.129 is also absolutely brilliant. Get this. A massive... 00:09:12.659 --> 00:09:15.820 62 % of their traffic comes from organic search. 00:09:16.299 --> 00:09:18.379 So people are actively out there searching for 00:09:18.379 --> 00:09:20.940 exactly this type of solution. They found a massive 00:09:20.940 --> 00:09:23.879 need. Plus, they effectively leverage TikTok 00:09:23.879 --> 00:09:26.639 and Instagram influencers, which makes perfect 00:09:26.639 --> 00:09:28.820 sense for reaching their student demographic. 00:09:28.940 --> 00:09:30.519 They are just everywhere their customer is looking. 00:09:30.740 --> 00:09:32.779 It's impressive. So from what we've seen with 00:09:32.779 --> 00:09:34.899 Aethor and others, what makes academic writing 00:09:34.899 --> 00:09:37.659 in particular such a perfect niche for an AI 00:09:37.659 --> 00:09:40.379 solution like this? It's a required skill. with 00:09:40.379 --> 00:09:43.019 specific, often difficult, formatting demands. 00:09:43.289 --> 00:09:46.169 OK, so after looking at these really incredible 00:09:46.169 --> 00:09:49.110 examples, Sheets Resume, Koopa, Ather, what does 00:09:49.110 --> 00:09:51.090 all of this mean for someone like you listening, 00:09:51.309 --> 00:09:53.129 maybe looking to build something similar? Our 00:09:53.129 --> 00:09:56.009 insights, they really highlight some very clear 00:09:56.009 --> 00:09:58.129 recurring patterns emerging from these successes. 00:09:58.490 --> 00:10:00.549 Yeah, definitely. First, and look, we keep coming 00:10:00.549 --> 00:10:02.350 back to this because it's so important, solve 00:10:02.350 --> 00:10:05.269 the whole problem. Don't just give people raw 00:10:05.269 --> 00:10:08.909 AI output and walk away. These successful companies, 00:10:08.909 --> 00:10:11.600 they solve the entire workflow. From that initial 00:10:11.600 --> 00:10:13.960 pain point, right through to seamless delivery. 00:10:14.480 --> 00:10:17.940 Second, know your customer deeply. Your own domain 00:10:17.940 --> 00:10:20.440 expertise, whatever it is, that's your unique 00:10:20.440 --> 00:10:22.799 advantage here. Sheets Resumes founder being 00:10:22.799 --> 00:10:25.139 a recruiter. Perfect example. Leverage what you 00:10:25.139 --> 00:10:28.440 know. Third, price for value, not just cost. 00:10:29.000 --> 00:10:30.720 Okay, AI generation might be getting cheaper, 00:10:31.080 --> 00:10:33.639 but the value your solution provides. That can 00:10:33.639 --> 00:10:35.919 be immense. Your pricing should reflect that 00:10:35.919 --> 00:10:38.870 value. Don't undercharge. And fourth, always 00:10:38.870 --> 00:10:40.789 plan for systematic growth within your niche. 00:10:41.289 --> 00:10:43.950 Don't just leap randomly to new features. Expand 00:10:43.950 --> 00:10:45.909 thoughtfully, serving your existing customer 00:10:45.909 --> 00:10:48.330 base more deeply. It really, really sounds like 00:10:48.330 --> 00:10:50.649 the technology itself, the underlying AI or the 00:10:50.649 --> 00:10:52.669 web stack isn't actually the biggest hurdle to 00:10:52.669 --> 00:10:55.330 getting started these days. Not at all. Honestly, 00:10:55.450 --> 00:10:57.850 the technological barrier to entry is incredibly 00:10:57.850 --> 00:11:00.149 low today. It's kind of democratized. Most of 00:11:00.149 --> 00:11:02.409 these successful businesses we looked at, they 00:11:02.409 --> 00:11:04.929 use a very standard web tech stack. something 00:11:04.929 --> 00:11:07.210 like React or maybe Vue for the front end, the 00:11:07.210 --> 00:11:09.669 part the user sees, then Node .js or Python on 00:11:09.669 --> 00:11:11.909 the backend for processing requests and connecting 00:11:11.909 --> 00:11:15.429 things. OpenAI's API or similar models from Anthropic 00:11:15.429 --> 00:11:18.710 or Google handles the core AI intelligence. For 00:11:18.710 --> 00:11:20.529 data storage, you're looking at standard stuff 00:11:20.529 --> 00:11:23.710 like PostgresWall or MongoDB. Stripe is almost 00:11:23.710 --> 00:11:26.309 always used for payment processing. And then 00:11:26.309 --> 00:11:28.730 standard cloud hosting like AWS, Google Cloud, 00:11:28.909 --> 00:11:31.889 or maybe Versel for simplicity beat. The beauty 00:11:31.889 --> 00:11:34.509 is you can genuinely build a basic functional 00:11:34.509 --> 00:11:37.590 version, an MVP, a minimum viable product in 00:11:37.590 --> 00:11:39.710 a matter of days or just a few weeks now. It's 00:11:39.710 --> 00:11:42.110 almost more like assembling Lego blocks of existing 00:11:42.110 --> 00:11:44.289 technology than inventing something totally new 00:11:44.289 --> 00:11:46.740 from scratch. That's quite a statement. So is 00:11:46.740 --> 00:11:49.019 the tech stack really that simple to set up for, 00:11:49.019 --> 00:11:51.399 say, a solo builder or maybe a very small team? 00:11:51.620 --> 00:11:54.500 Yes, absolutely. Modern tools and even no -code 00:11:54.500 --> 00:11:57.139 or low -code platforms make basic versions buildable 00:11:57.139 --> 00:12:00.250 in weeks, sometimes even faster. Okay. And our 00:12:00.250 --> 00:12:02.610 research also provides a pretty clear, actionable 00:12:02.610 --> 00:12:05.509 plan for anyone interested in actually pursuing 00:12:05.509 --> 00:12:07.549 this. It's broken down into distinct phases. 00:12:07.710 --> 00:12:09.889 Yeah, it's pretty straightforward, really. Phase 00:12:09.889 --> 00:12:12.950 one is all about research and validation. Super 00:12:12.950 --> 00:12:15.850 critical. Start by identifying your own expertise. 00:12:15.909 --> 00:12:18.610 What do you know really well? Then, within that 00:12:18.610 --> 00:12:21.700 area, find genuine Pain points. Talk to people. 00:12:22.179 --> 00:12:24.620 Research the existing competition. What's out 00:12:24.620 --> 00:12:27.320 there? How are they falling short? And crucially, 00:12:27.639 --> 00:12:29.679 validate that there's real demand for a better 00:12:29.679 --> 00:12:32.940 solution. Don't build in a vacuum. Then, phase 00:12:32.940 --> 00:12:36.639 two. Planning and design. Define your specific 00:12:36.639 --> 00:12:39.100 solution in detail. What will it actually do? 00:12:39.460 --> 00:12:42.240 Plan your minimum viable product, your MVP, and 00:12:42.240 --> 00:12:44.240 be ruthless here. What's the absolute smallest 00:12:44.240 --> 00:12:46.340 version that still completely solves that core 00:12:46.340 --> 00:12:49.220 problem you identified? Don't overbuild. Then 00:12:49.220 --> 00:12:50.940 choose your business model one -time subscription 00:12:50.940 --> 00:12:53.539 and design a truly intuitive user experience. 00:12:53.659 --> 00:12:55.639 Make it as simple and delightful as possible. 00:12:56.000 --> 00:12:57.860 And then logically comes the building and the 00:12:57.860 --> 00:13:00.240 growth phase. Exactly. Set up that technical 00:13:00.240 --> 00:13:02.059 foundation we talked about, the Lego blocks. 00:13:02.539 --> 00:13:05.360 Integrate your chosen AI capabilities. Build 00:13:05.360 --> 00:13:08.100 those core MVP features first. Nothing else. 00:13:08.799 --> 00:13:11.580 And test everything rigorously. Test, test, test. 00:13:12.200 --> 00:13:16.120 Beat. Then maybe do a soft launch. Get it into 00:13:16.120 --> 00:13:18.240 the hands of real users. Maybe a small group 00:13:18.240 --> 00:13:21.019 first. Gather their feedback mercilessly. Be 00:13:21.019 --> 00:13:23.899 open to criticism. Iterate based on what they 00:13:23.899 --> 00:13:26.600 tell you. And then focus heavily on marketing 00:13:26.600 --> 00:13:29.750 and expansion. Think about SEO from day one, 00:13:30.169 --> 00:13:32.669 targeted social media, maybe strategic influencer 00:13:32.669 --> 00:13:35.049 partnerships like Aethor did. That's how you 00:13:35.049 --> 00:13:37.649 scale up. That makes sense. Thinking about that 00:13:37.649 --> 00:13:40.269 MVP stage again, what's maybe the biggest mistake 00:13:40.269 --> 00:13:42.570 you see new builders often make when they're 00:13:42.570 --> 00:13:44.759 planning that initial version? Oh, easy. trying 00:13:44.759 --> 00:13:46.879 to build too many features instead of just relentlessly 00:13:46.879 --> 00:13:48.820 focusing on solving that core problem really, 00:13:48.820 --> 00:13:50.980 really well. Right, the focus again. So if we 00:13:50.980 --> 00:13:52.620 try to distill everything we've talked about 00:13:52.620 --> 00:13:54.419 today, all these examples, all these patterns, 00:13:54.919 --> 00:13:56.899 what's the big idea here? What's the core takeaway? 00:13:57.159 --> 00:14:00.539 It's this. Simple AI wrappers, the ones people 00:14:00.539 --> 00:14:03.929 sometimes dismiss. They are absolute potential 00:14:03.929 --> 00:14:07.149 goldmines. They succeed by specializing deeply 00:14:07.149 --> 00:14:09.750 in a particular niche, solving the complete problem 00:14:09.750 --> 00:14:12.110 for their users, not just part of it, pricing 00:14:12.110 --> 00:14:14.450 for the immense value they provide, and planning 00:14:14.450 --> 00:14:16.629 for systematic, thoughtful growth within that 00:14:16.629 --> 00:14:19.909 chosen niche. It always, always comes back to 00:14:19.909 --> 00:14:22.309 truly knowing your customers. Understanding their 00:14:22.309 --> 00:14:24.809 needs, their workflows, their journey, inside 00:14:24.809 --> 00:14:27.169 and out. That's the secret sauce. And the future 00:14:27.169 --> 00:14:29.389 of these wrappers, it isn't static, is it? It 00:14:29.389 --> 00:14:31.490 seems like it's evolving really rapidly. We're 00:14:31.490 --> 00:14:33.409 definitely going to see increased specialization, 00:14:33.590 --> 00:14:36.610 even more niche tools, even more seamless integration 00:14:36.610 --> 00:14:38.870 into existing professional workflows so they 00:14:38.870 --> 00:14:40.649 just become part of the fabric of how people 00:14:40.649 --> 00:14:43.610 work. And the rise of multimodal AI, you know, 00:14:43.710 --> 00:14:46.409 combined text, images, maybe even video, in powerful 00:14:46.409 --> 00:14:48.690 new ways. Expect to see highly sophisticated, 00:14:49.009 --> 00:14:50.850 industry -specific solutions emerge for things 00:14:50.850 --> 00:14:55.120 like law, medicine, finance, be - whoa. Imagine 00:14:55.120 --> 00:14:57.919 these tools scaling to handle a billion queries 00:14:57.919 --> 00:15:00.460 a day. The scale is potentially massive. Exactly. 00:15:00.659 --> 00:15:02.659 The opportunity isn't disappearing. Not at all. 00:15:02.879 --> 00:15:05.779 It's just shifting, evolving. And frankly, it's 00:15:05.779 --> 00:15:08.320 only getting more interesting. And we also need 00:15:08.320 --> 00:15:10.639 to touch on the ethical side briefly. Ah, yes. 00:15:10.820 --> 00:15:12.799 Absolutely. Important point, especially with 00:15:12.799 --> 00:15:15.539 AI. Definitely. Academic integrity, especially 00:15:15.539 --> 00:15:18.899 with tools like ATHOR. It's crucial to position 00:15:18.899 --> 00:15:22.360 your tool. As an assistant, a helper, not a replacement 00:15:22.360 --> 00:15:24.840 for critical thinking or original work, data 00:15:24.840 --> 00:15:27.259 privacy is massive too. You have to be transparent 00:15:27.259 --> 00:15:29.789 about how you use user data. Secure it properly. 00:15:30.350 --> 00:15:33.230 And AI bias is a real thing. These models can 00:15:33.230 --> 00:15:35.269 inherit biases from the data they're trained 00:15:35.269 --> 00:15:36.929 on. You need to be aware of that. Heck, I still 00:15:36.929 --> 00:15:39.009 wrestle with prompt drift myself sometimes, where 00:15:39.009 --> 00:15:42.070 the AI's output changes unexpectedly. So understanding 00:15:42.070 --> 00:15:45.110 these limitations and biases is critical. Very 00:15:45.110 --> 00:15:48.789 important considerations. So the only real question 00:15:48.789 --> 00:15:52.070 left for you listening now is this. What problem 00:15:52.070 --> 00:15:55.100 will you solve? Take some time, maybe after this, 00:15:55.279 --> 00:15:57.480 to really think about your own unique expertise, 00:15:58.000 --> 00:16:00.360 the industry you know best, or even just the 00:16:00.360 --> 00:16:02.500 daily frustrations you see or encounter yourself. 00:16:03.120 --> 00:16:05.399 The next million -dollar AI solution might just 00:16:05.399 --> 00:16:07.259 be hiding there in plain sight, just waiting 00:16:07.259 --> 00:16:09.480 for you to uncover it. Absolutely. Thanks for 00:16:09.480 --> 00:16:11.059 joining us on this deep dive, everyone. We'll 00:16:11.059 --> 00:16:11.600 see you next time.